Image stitch algorithm based on SIFT and MVSC

Based on scale-invariant feature transform (SIFT) and mean seamless cloning (MVSC), an image stitching algorithm is presented, to improve the quality of the panoramic stiching image. Using SIFT algorithm to extract between benchmark images (await matched image) and follow-up images(with the baseline image match the image) of the feature points, identifying locations and directions, using 128 dimensional vector to describe features point. Using the nearest neighbor method to achieve two images feature point matching, identify overlap regions. Using SIFT algorithm to provide benchmark images and follow-up images to determine the source cloning domain and target cloning domain of the MVSC. Using the mean value coordinates to achieve the pixel to interpolat from the source cloning domain to target cloning domain. Finally, using MVSC algorithm to achieve the two images stitching. Experiment results shows that this method with regard to image rotation, perspective changes and image scaling to have a very good stitching results, stitching image is complete information, the quality of the image is high.